Computational Genomics Research Scientist

Role Summary

We are seeking a computational biologist with a strong track record of advancing biological discoveries through data analyses to join Vertex Data and Computational Sciences (DCS). In this role, you will leverage cutting-edge computational biology to accelerate the development of transformative therapies for serious human diseases. You will design genomics and human genetic studies, develop and apply analytical methods, and interpret results that directly inform program strategy, target evaluation, and mechanistic understanding. This is a San Diego-based, hybrid position requiring 3 days per week onsite.

Responsibilities

• Proactively collaborate with cross-functional project teams as the computational biology expert to identify key scientific questions that can be addressed through human genetics, genomics, sequencing, and computational analyses.
• Design and execute studies across diverse omics, including bulk RNA-seq, whole-genome sequencing, single-cell RNA-seq, spatial transcriptomics, and human genetics.
• Perform sophisticated computational analyses of internal and external datasets, integrating deep critical thinking, statistical rigor, domain expertise, and best practices from the literature to generate actionable insights.
• Incorporate publicly available genomic resources (e.g., GTEx, gnomAD, FinnGen, UK Biobank) to contextualize and interpret internal data.
• Distill complex analyses and scientific results into clear presentations, including key take-home messages and recommendations for next steps to a broad audience.
• Author study reports, white papers, and manuscripts to support internal decision-making and external communications including regulatory filings.
• Partner with the DCS method development team to develop innovative methods and improve usability, accuracy, and robustness of existing ones.

Qualifications

• A proven track record in the analysis, visualization, and interpretation of genomic and next-generation sequencing (NGS) data
• Solid scientific understanding of gene editing, the role of genetic variation in human disease, molecular biology, and cellular biology
• Expertise with applying computational methods and bioinformatics tools to large-scale data
• Solid understanding of statistics
• Demonstrated ability to work across cross-functional teams, ensuring timely progress
• Superior communication skills, demonstrating confidence and versatility in presenting verbally to diverse audiences and writing technical documents
• Deep scientific understanding of genetic variation in human disease, molecular biology, and cellular biology
• Expertise with rapidly applying computational methods and bioinformatics tools to large-scale data
• Proficiency with R and/or Python, and high-performance computing systems; solid understanding of statistics
• A team-oriented growth mindset that welcomes feedback from others and supports other team members

Skills

• Genomic data analysis, visualization, and interpretation
• Computational methods and bioinformatics tooling for large-scale datasets
• Statistical analysis and interpretation in a biomedical context
• Communication of complex scientific concepts to diverse audiences
• Cross-functional collaboration and teamwork
• Programming in R and/or Python; experience with high-performance computing

Education

• PhD degree (or Master’s degree) in computational biology, bioinformatics, human genetics, genomics, systems biology, bioengineering, or a related field with 0–3 years (or 3+ years for Master’s degree) of productive, relevant industry or post-doc experience
• A proven track record of stand-out excellence in the analysis, visualization, and interpretation of genomic data (such as next-generation sequencing (NGS)) or human genetic data
• Demonstrated ability to work across cross-functional teams, ensuring timely progress
• Deep scientific understanding of genetic variation in human disease, molecular biology, and cellular biology
• Expertise with rapidly applying computational methods and bioinformatics tools to large-scale data
• Proficiency with R and/or Python, and high-performance computing systems; solid understanding of statistics
• A team-oriented growth mindset that welcomes feedback from others and supports other team members